AbstractIn this paper, the multilinear normal distribution is introduced as an extension of the matrix-variate normal distribution. Basic properties such as marginal and conditional distributions, moments, and the characteristic function, are also presented. A trilinear example is used to explain the general contents at a simpler level. The estimation of parameters using a flip-flop algorithm is also briefly discussed
In this paper we give a characterization of the multivariate normal distribution through the conditi...
Fractional matrix operator methods are introduced as a new tool of distribution theory for use in mu...
AbstractThe noncentral distributions of Y = Πi=1p θia(1 − θi)b are obtained, where a and b are known...
In this paper, the multilinear normal distribution is introduced as an extension of the matrix-varia...
AbstractIn this paper, the multilinear normal distribution is introduced as an extension of the matr...
Title: Multivariate Normal Distribution Author: Jakub Ježo Department: Department of Probability and...
We briefly summarize the definitions of univariate and multivariate normal distributions, along with...
In this paper, we define a new class of multivariate skew-normal distributions. Its properties are s...
The normal-Laplace distribution is considered and its properties are discussed. A multivariate norma...
The thesis deals with the basic discrete and continuous multivariate distributions, which play an im...
The paper extends earlier work on the so-called skew-normal distribution, a family of distributions ...
The paper extends earlier work on the so-called skew-normal distribution, a family of distributions ...
AbstractThis article proposes a class of weighted multivariate normal distributions whose probabilit...
AbstractA general real matrix-variate probability model is introduced here, which covers almost all ...
The problem of determining a statistical population belonging to a certain class of distributions is...
In this paper we give a characterization of the multivariate normal distribution through the conditi...
Fractional matrix operator methods are introduced as a new tool of distribution theory for use in mu...
AbstractThe noncentral distributions of Y = Πi=1p θia(1 − θi)b are obtained, where a and b are known...
In this paper, the multilinear normal distribution is introduced as an extension of the matrix-varia...
AbstractIn this paper, the multilinear normal distribution is introduced as an extension of the matr...
Title: Multivariate Normal Distribution Author: Jakub Ježo Department: Department of Probability and...
We briefly summarize the definitions of univariate and multivariate normal distributions, along with...
In this paper, we define a new class of multivariate skew-normal distributions. Its properties are s...
The normal-Laplace distribution is considered and its properties are discussed. A multivariate norma...
The thesis deals with the basic discrete and continuous multivariate distributions, which play an im...
The paper extends earlier work on the so-called skew-normal distribution, a family of distributions ...
The paper extends earlier work on the so-called skew-normal distribution, a family of distributions ...
AbstractThis article proposes a class of weighted multivariate normal distributions whose probabilit...
AbstractA general real matrix-variate probability model is introduced here, which covers almost all ...
The problem of determining a statistical population belonging to a certain class of distributions is...
In this paper we give a characterization of the multivariate normal distribution through the conditi...
Fractional matrix operator methods are introduced as a new tool of distribution theory for use in mu...
AbstractThe noncentral distributions of Y = Πi=1p θia(1 − θi)b are obtained, where a and b are known...